Distribution Fault Anticipation (DFA) Technology Second Annual Smart Grid Research Consortium Conference: “Evaluating the Business Case for Smart Grid” sponsored by Smart Grid Consortium Orlando, Florida, October 21, 2011 John S. Bowers, PE Vice President of Operations Pickwick Electric Cooperative PO Box 49, 530 Mulberry Street Selmer, TN 38375 731-646-3766
[email protected]
Carl L. Benner, PE Senior Research Engineer Dept. of Electrical and Computer Engineering 3128 TAMU, Texas A&M University College Station, TX 77843-3128 979-845-6224
[email protected] DFA Technology Success Stories are available at: https://epridfa.tamu.edu/DFAReports/DFASuccess.aspx
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Overview of DFA Technology • Background: Technology’s foundation lies in EPRI’s DFA (Distribution Fault Anticipation) project, performed by Texas A&M, in close cooperation with multiple utilities. DFA label persists for historical reasons. • Substation-based DFA devices sense high-fidelity current and voltage waveforms, using conventional CTs and PTs. • DFA devices execute on-line algorithms that analyze waveforms to diagnose failures, maloperations, etc. • DFA system provides actionable reports about “important” line activity. • The result: Awareness of system conditions, including incipient faults and outages. Copyright © 2011. The Texas A&M University System.
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Utility Partners Hardware Demonstration Sites Arizona Public Service BC Hydro Bryan Texas Utilities CenterPoint Energy ConEdison CPS Energy Exelon KeySpan Energy MidAmerican Energy Northeast Utilities Omaha Public Power District Oncor Electric Delivery Southern Company/Alabama Power TVA/Pickwick Electric Cooperative
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Other Previous/Current Partners American Electric Power Baltimore Gas & Electric (Constellation) Central Hudson Gas & Electric FirstEnergy Public Service Electric & Gas
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Conceptual Application of Intelligent Algorithms to Electrical Waveforms Fault Anticipation
Diagnosis of Protection Problems
Condition-Based Maintenance
Forensics
Asset Management
Intelligent Algorithms (Analytics)
O&M Cost Reduction
Improved Power Quality Improved Safety Outage Management
Reliability
Substation waveforms “know” about feeder activity. They can provide system awareness, if we measure them with sufficient fidelity and know how to interpret them. Copyright © 2011. The Texas A&M University System.
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Documented Failures •Voltage regulator failure •LTC controller maloperation •Repetitive overcurrent faults •Lightning arrester failures •Switch and clamp failures •Cable failures
•Pole-top xfmr bushing failure •Pole-top xfmr winding failure •URD padmount xfmr failure •Bus capacitor bushing failure •Capacitor problems
– Controller maloperation – Failed capacitor cans – Main substation cable – Blown fuses – URD primary cables – Switch restrike – URD secondary cables – Switch sticking – Overhead secondary cables – Switch burn-ups •Tree/vegetation contacts – Switch bounce – Contacts with primary Certain types of failures occur frequently and well understood. Other types of – are Pack failure – Contacts with secondary failures occur infrequently and only one or a few incidents have been servicesOngoing field experience enables continuous improvement and documented. next-generation DFA algorithms to diagnose those types of failures better. Copyright © 2011. The Texas A&M University System.
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We All Need More Data – Not!
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Inputs: Substation CT and PT Waveforms
DFA Algorithms
On-Line Signal Processing and Pattern Recognition Algorithms
Performed by DFA device in substation
DFA Reports
Line recloser* tripped 8% of phase-A load twice, but reclosed and did not cause outage
Failed 1200 kVAR line capacitor* (phase B inoperable) Failing hot-line clamp on phase B*
*DFA system reports hydraulic reclosers, switched line capacitors, line apparatus failures, etc, based on substation waveforms, without requiring communications to those devices. Copyright © 2011. The Texas A&M University System.
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DFA Web-Based Reporting Format Reading Reported Protection Sequence (Hydraulic Line Recloser): • Single-phase line recloser operated three times and locked out. • Fault was phase-B and drew 745 amps. • Sequence was fast-slow-slow (3 cycles, 12 cycles, 10-1/2 cycles). • Open intervals were 2.1 and 2.4 seconds. • Each operation temporarily interrupted half of phase-B load. (Sequence of events below was created by DFA, not by humans.)
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DFA Web-Based Reporting Format Waveforms are available for viewing and further analysis, if desired.
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Utility Perspective
UTILITY EXPERIENCE WITH DFA
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Pickwick Electric Cooperative • Rural electric coop Headquartered in Selmer, Tennessee, home of Shiloh National Military Park, Pickwick Dam, and Pickwick Lake Southwest corner of Tennessee, 100 miles east of Memphis Customer of Tennessee Valley Authority 21,000 customers; 2,000 miles of distribution
• TVA’s participant in research behind DFA technology EPRI-funded project at Texas A&M Five feeders instrumented with DFA
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Example
MYSTERIOUS SERVICE PROBLEM REQUIRES FOUR TRUCK ROLLS Copyright © 2011. The Texas A&M University System.
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Example Mysterious Service Problem • T=0 hours: 16 customers with lights out Blown tap fuse, but no obvious system failure. New fuse holds. Close ticket.
• T=36 hours: Flickering lights in same area Crew hears buzzing transformer. Replace transformer. No buzzing. Close ticket.
• T=38 hours: Lights flickering again
Now what do I do? Copyright © 2011. The Texas A&M University System.
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Example Mysterious Service Problem •
For three weeks, the DFA system had been reporting a failing clamp on this phase of this circuit.…
•
… but the dispatcher and crew were unaware of the DFA report. This was a missed opportunity. Moving forward, providing information to right people can provide awareness and ...
•
– –
Reduce complaints and truck rolls. Reduce unnecessary equipment changeouts.
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Example
INCIPIENT FAILURES AND AVOIDABLE OUTAGES Copyright © 2011. The Texas A&M University System.
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Example Avoidable Outage – Without DFA • • • • • • •
6/03/06 6/10/06 6/17/06 6/24/06 6/28/06 7/04/06 7/24/06
First fault; no outage Second fault; no outage Third fault; no outage Fourth fault; no outage Similar but unrelated fault Fifth fault; no outage Sixth fault; outage
6/03/06
6/10/06
7/24/06
– 35 minutes, 903 customers – 31,605 CMI Copyright © 2011. The Texas A&M University System.
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Example Avoided Outage – With DFA •Similar faults two days apart •Next day – Alerted by DFA – Using DFA, found problem in 1 hr – Avoided consequences • Additional interruptions • Extended outage • Punch-through, moisture ingress • Lid launch, burning oil, fire hazard
•7th day: Third fault prioritized repair •No outage, complaints, or further consequences Copyright © 2011. The Texas A&M University System.
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Detailed Example Avoided Outage – With DFA
Feeder NS 344 (139 circuit miles) R
Sub
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Step 1: Learn of recurrent fault from DFA DFA reported identical faults, 18 days apart Step 2: Compare DFA info to system model at various reclosers (e.g., recloser R) Protection – DFA: Reported operation of 1ø recloser – Model: R is bank of 1ø hydraulic reclosers Momentary Load Interruption – DFA: Estimated 19-21% load interruption – Model: 23% of load is beyond R Reclosing Interval – DFA: Reported 2-second open interval – Model: Reclosers at R have 2-second open Conclusion: Failure is downstream of recloser R (26% of total feeder length). 18
R Enlarged View of Line Downstream of R
X
DB
•
Initial patrol downstream of R visually identified cracked dead-end bells (DB), but… – DFA fault-current estimate @ DB: 510A – Model fault-current estimate @ DB: 1086A Then, using DFA fault-current estimate of 510A, model targeted area outlined in oval (~2% of total feeder).
X
•
NS 344 (139 circuit miles)
R Sub
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Enlarged View of Oval
NS 344 (139 circuit miles)
R Sub
Manually integrating DFA information with system model put failure in oval area, encompassing 4 spans on either side of a tee. Searching that small area found this failing arrestor. Replacing it avoided further interruptions and likely outage to 53 customers. Copyright © 2011. The Texas A&M University System.
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Recurrent Faults – A Recap • DFA can detect failing apparatus and avoid outages. – DFA often provides sole notice of problem. Without that, nothing else matters. – Just counting faults on a feeder is insufficient. It is necessary to know that a specific fault is recurring.
• Integrating DFA information with system model locates failure. – For the subject case, this located failure within four spans, on feeder with total of 139 circuit miles. – Process is straightforward, but manual application is tedious.
• Might it be feasible to automate the process of integrating DFA information with a system model, to streamline the process of learning of and locating these pre-failures? It would seem so. • Important: This process locates failures that have not caused outages and that often have not generated customer calls, thereby making it feasible to avoid many outages. Copyright © 2011. The Texas A&M University System.
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Example
FAULTY CAPACITOR CONTROLLER RESULTS IN EQUIPMENT DAMAGE AND DEGRADED POWER QUALITY Copyright © 2011. The Texas A&M University System.
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Example Capacitor Problem – Without DFA • 1/2004: 28 cycles per day • 2/2004: 100 cycles per day • 2/29/2004-3/3/2004 Switch contacts arced three days Severe voltage transients Failures in other cap banks • Final consequences 3,000 cycles in two months Failed switch Four damaged capacitor banks
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Example Capacitor Problem – With DFA • 8/9/2004 Capacitor controller was changed out during normal maintenance. Hours after crew left, controller began switching bank continuously. • 8/10/2004 DFA reported 22 switching events. Crew corrected controller settings. Continuous switching stopped. Copyright © 2011. The Texas A&M University System.
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Example
Feeder Lockouts Resulting from Protection Miscoordination (or Maybe Not!) Copyright © 2011. The Texas A&M University System.
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Example Improper Breaker Lockouts • Remote fault tripped mid-point line recloser, but breaker tripped, too, locking out feeder. • Utility performed lengthy investigation. Result: “Cause Unknown.” • Two years later, same thing happened again. • This time, the DFA system helped utility to identify and locate fault-induced conductor slap (FICS). • (FICS: Distant fault trips mid-point recloser, but magnetic forces cause close-in wires to swing together, creating second fault.) Copyright © 2011. The Texas A&M University System.
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Example Improper Breaker Lockouts
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Example Improper Breaker Lockouts
• DFA reports conductor-slap and enables location. • Result: Utility can alter the offending line segment, thereby preventing future breaker operations and feeder lockouts. Copyright © 2011. The Texas A&M University System.
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Another Conductor-Slap Example
0 0.3
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Facts (this case): • Four conductor-slap incidents • Eight unnecessary breaker trips • Same location on same feeder • Breaker tripped two times for each event • Phenomenon was not discovered by conventional tools available to utilities
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Months
Ramifications (in general): • Conductor-slap and fault will recur in future. • Progressive conductor damage, with possibility of conductor burn-down • Stress on all current-carrying components (switches, connectors, …) • Fire hazard from burning aluminum particles
A significant finding has been that slap does not happen at random locations on feeders. Locations experiencing slap once, left uncorrected, likely will experience it again and again, repeatedly creating system stresses and the chance of prolonged outages, fire, etc. Copyright © 2011. The Texas A&M University System.
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Example
INTERMITTENT FAILURE OF BREAKER TO RECLOSE RESULTS IN MULTIPLE SUSTAINED OUTAGES Copyright © 2011. The Texas A&M University System.
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Example Feeder Breaker Fails to Reclose • • • • • • • •
04/08/10: Breaker operates properly. 08/06/10: Breaker operates properly. 10/19/10: Breaker fails to auto-reclose. 12/10*: Standard tests show no problem. 01/08/11: Breaker fails to auto-reclose. 03/06/11: Breaker operates properly. 03/18/11: Breaker fails to auto-reclose. 03/26/11: Breaker operates properly.
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Examples: Other Anomalies • Case 1: Line burned down past line recloser and autosectionalizer. DFA helped determine which device failed. • Case 2: In multiple cases, utility has used DFA to determine whether questionable reclosers were functioning properly, without removing them for offline testing. • Case 3: DFA report is helping ongoing investigation to diagnose why a self-healing circuit did not respond properly. • Case 4: DFA helped utility identify that a three-phase recloser had stopped mid-sequence, failing to reclose or lock out, creating hazard for a crew that assumes open recloser is locked out.
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Possible Future Algorithms • Continual process of discovering new signatures and expanding capabilities is inherent in DFA technology’s future roadmap. • Fundamental design of system anticipates and accommodates future extensions of capabilities. • For example, Texas A&M currently is evaluating potential unique characteristics for… – Lightning-induced faults. – Arrester-induced faults.
Copyright © 2011. The Texas A&M University System.
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Benefit Estimates (Partial List)
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Conclusions • DFA technology provides advanced on-line diagnostics, creating awareness we never had before. • We are dealing with new types of information, not previously envisioned. New processes and procedures may be required. • Utilities are using DFA to avoid outages and better diagnose other problems, but need better access to reports to enable them to take full advantage. • New EPRI project is addressing issues regarding when and how to deliver information, for best use and impact. • Field installations continue to provide data for discovery of new “fingerprints” and better diagnosis and reporting. Copyright © 2011. The Texas A&M University System.
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Contact Information
John S. Bowers, PE Vice President of Operations Pickwick Electric Cooperative PO Box 49, 530 Mulberry Street Selmer, TN 38375 731-646-3766
[email protected]
Carl L. Benner, PE Senior Research Engineer Dept. of Electrical and Computer Engineering 3128 TAMU, Texas A&M University College Station, TX 77843-3128 979-845-6224
[email protected]
DFA Technology Success Stories are available at: https://epridfa.tamu.edu/DFAReports/DFASuccess.aspx Copyright © 2011. The Texas A&M University System.
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